Abstract
In panel data analysis, the cross-sectional dependence (CD) test has been extensively used to test the cross-sectional dependence. However, this traditional CD test does not take serial correlation into consideration, which commonly occurs in many fields. To solve this problem, we propose an adjusted CD test which is able to effectively handle serial correlation. More specifically, the serial correlation can be of arbitrary form in our work. Furthermore, we establish the theoretical properties of the proposed adjusted CD test. Our extensive Monte Carlo experiments show that the traditional CD test cannot work well under serial correlation, while the proposed adjusted CD test does provide rather satisfactory performance.
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Acknowledgements
This work was supported by National Natural Science Foundation of China (Grant Nos. 11001225, 11401482 and 71532001).
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Lan, W., Pan, R., Luo, R. et al. High dimensional cross-sectional dependence test under arbitrary serial correlation. Sci. China Math. 60, 345–360 (2017). https://doi.org/10.1007/s11425-014-0731-4
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DOI: https://doi.org/10.1007/s11425-014-0731-4